6688e1c23b
2. An initial introduction of InterpreterDetailedStatus to detail the error code that a TFLite interpreter may have during runtime. 3. Apply the above two to instrument the overall invoke latency and status as an initial exemplar usage. PiperOrigin-RevId: 313573701 Change-Id: I8c4189c72066d7d6f4c91014ef4f30e32635c115
47 lines
1.5 KiB
C++
47 lines
1.5 KiB
C++
/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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==============================================================================*/
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#ifndef TENSORFLOW_LITE_PROFILING_NOOP_PROFILER_H_
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#define TENSORFLOW_LITE_PROFILING_NOOP_PROFILER_H_
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#include <vector>
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#include "tensorflow/lite/core/api/profiler.h"
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#include "tensorflow/lite/profiling/profile_buffer.h"
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namespace tflite {
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namespace profiling {
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// A noop version of profiler when profiling is disabled.
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class NoopProfiler : public tflite::Profiler {
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public:
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NoopProfiler() {}
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explicit NoopProfiler(int max_profiling_buffer_entries) {}
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uint32_t BeginEvent(const char*, EventType, int64_t, int64_t) override {
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return 0;
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}
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void EndEvent(uint32_t) override {}
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void StartProfiling() {}
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void StopProfiling() {}
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void Reset() {}
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std::vector<const ProfileEvent*> GetProfileEvents() { return {}; }
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};
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} // namespace profiling
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} // namespace tflite
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#endif // TENSORFLOW_LITE_PROFILING_NOOP_PROFILER_H_
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